|
|
|
| R2012a Documentation → Global Optimization Toolbox | |
Learn more about Global Optimization Toolbox |
|
| Contents | Index |
This table summarizes what's new in Version 3.0 (R2010a).
| New Features and Changes | Version Compatibility Considerations | Fixed Bugs and Known Problems |
|---|---|---|
Yes | Yes–Details labeled as Compatibility Considerations, below. See also Summary. | Bug
Reports Includes fixes |
New features and changes introduced in this version are described here:
Former Genetic Algorithm and Direct Search Toolbox™ functions are now part of Global Optimization Toolbox software.
Error and warning IDs now use the globaloptim name instead of the gads name. For example, to turn off the sahybrid:unconstrainedHybridFcn warning, instead of
warning('off','gads:sahybrid:unconstrainedHybridFcn')use the statement
warning('off','globaloptim:sahybrid:unconstrainedHybridFcn')GlobalSearch and MultiStart run a local solver (such as fmincon) from a variety of start points. The goal is to find a global minimum, or multiple local minima. The chief differences between the solver objects are:
GlobalSearch uses a scatter-search mechanism for generating start points. MultiStart uses uniformly distributed start points within bounds, or user-supplied start points.
GlobalSearch analyzes start points and rejects those that are unlikely to improve the best local minimum found so far. MultiStart runs all start points.
MultiStart gives a choice of local solver: fmincon, fminunc, lsqcurvefit, or lsqnonlin. GlobalSearch uses fmincon.
MultiStart can be run in parallel, distributing start points to multiple processors. GlobalSearch does not run in parallel.
These solver objects come with a variety of new objects, functions, and methods:
createOptimProblem — Function for creating optimization problem structure
CustomStartPointSet and RandomStartPointSet — Objects for MultiStart multiple start points
GlobalOptimSolution — Object for holding results of multiple runs of local solver
list — Method for obtaining start points from a CustomStartPointSet or RandomStartPointSet
run — Method for running GlobalSearch or MultiStart objects with optimization problem structures
For more information, see Using GlobalSearch and MultiStart in the Global Optimization Toolbox User's Guide.
A new poll method generates search directions faster and more reliably in patternsearch for linearly constrained problems. Use this poll method at the command line by setting the PollMethod option to 'GSSPositiveBasis2N' or 'GSSPositiveBasisNp1' with psoptimset. With the Optimization Tool, set Options > Poll > Poll method to GSS Positive basis 2N or GSS Positive basis Np1.
For more information, see Poll Options in the Global Optimization Toolbox User's Guide.
There is a new demo showing how to use GlobalSearch and MultiStart to find a global optimum or several local optima. Run the demo at the MATLAB command line by entering echodemo opticalInterferenceDemo.
The threshacceptbnd function has been removed.
Use simulannealbnd for similar functionality. To obtain results using a threshold acceptance algorithm, write a custom acceptance function for simulannealbnd—see AcceptanceFcn in Algorithm Settings.
 | Version 3.1 (R2010b) Global Optimization Toolbox Software | Version 2.4.2 (R2009b) Genetic Algorithm and Direct Search Toolbox Software |  |
Learn how to use optimization to solve systems of equations, fit models to data, or optimize system performance.
Get free kit| © 1984-2012- The MathWorks, Inc. - Site Help - Patents - Trademarks - Privacy Policy - Preventing Piracy - RSS |